Skip to content
Data warehouse

Apache Kylin to BigQuery integration — real-time data sync

Keep Apache Kylin and BigQuery in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Apache Kylin and BigQuery

Keep tables consistent across Apache Kylin and BigQuery, for a migration, a multi-warehouse stack, or a dataset two platforms both need.

Apache Kylin is a read-only source: Stacksync reads its data in real time and delivers it into BigQuery, so BigQuery always reflects the current state of Apache Kylin — without exports, scripts, or schedulers.

Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.

Common use cases

  • Read pre-aggregated metrics from Kylin and sync them into CRM fields or planning spreadsheets on a schedule.
  • Expose Kylin query results to operational dashboards without granting access to the underlying Hadoop data.
  • Land CRM and ERP records in BigQuery continuously so dashboards reflect business systems without nightly batch jobs
  • Activate modeled BigQuery tables by syncing computed attributes back into sales and marketing tools

Serve tools that only connect to one platform

Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.

Shared datasets across teams

Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.

Consolidation after M&A

Bring the acquired company's warehouse data across continuously instead of through one-off dumps.

What you can sync between Apache Kylin and BigQuery

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Apache Kylin objects BigQuery objects
Segments Time-ranged build units that partition pre-computed data. Partitioned tables Synced like regular tables; partition columns map to target fields.
Build Jobs Batch jobs that compute or refresh segments, monitored via the REST API. Clustered tables Supported; clustering is transparent to the sync.
Projects Top-level workspaces that group models, tables, and jobs. Datasets Organizational container — you pick which dataset’s tables to sync.
Models Star-schema definitions over source tables that determine what can be queried. Projects Connection scope: the service account grants access per project.
Cubes / Indexes Pre-computed aggregate structures that answer queries at low latency. Tables The syncable unit: only tables can be synced per the Stacksync docs.
What ships with Apache Kylin ⇄ BigQuery

Connect Apache Kylin and BigQuery for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Kylin–BigQuery connection.

Real-time

Real-time sync

Changes in Apache Kylin or BigQuery instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Kylin or BigQuery data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Apache Kylin or BigQuery record.

Observability

Monitoring

Track your Apache Kylin ⇄ BigQuery sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Kylin and BigQuery.

How the Apache Kylin and BigQuery connectors work

Apache Kylin

Integration surface
SQL over JDBC/ODBC plus a REST API for queries and administration
Authentication
Username/password (HTTP basic authentication on the REST API)
Change detection
Not applicable for row-level capture; data freshness follows segment build and refresh jobs, so integrations poll query results
Capabilities
read
Rate limits
No fixed API quotas; query capacity depends on the deployment and pre-computed index coverage

BigQuery

Integration surface
GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication
Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver
Change detection
Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen") with a Cloud Run "secure portal for real-time notification service in
Capabilities
read · write · CDC
Rate limits
Subject to Google Cloud quotas on queries, DML, and streaming; DML is supported but the platform favors append-heavy batch and streaming loads over row-at-a-time writes
BigQuery setup guide
How it works

How to connect Apache Kylin to BigQuery — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Apache Kylin and BigQuery with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Apache Kylin connected
    BigQuery connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Apache Kylin and BigQuery objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Apache Kylin ⇄ BigQuery
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Apache Kylin BigQuery
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
Try interactive demo
FAQ

Apache Kylin and BigQuery integration FAQ

SECURITY

Security teams love Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Kylin and BigQuery.

Popular · 8 of 386
All Apache Kylin integrations All BigQuery integrations Browse all integrations
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.

Book a demo Tour the platform on your own